When a CIA-backed venture capital fund took an interest in Rana el Kaliouby’s face-scanning technology for detecting emotions, the computer scientist and her colleagues did some soul-searching — and then turned down the money.

“We’re not interested in applications where you’re spying on people,” said el Kaliouby, the CEO and co-founder of the Boston startup Affectiva. The company has trained its artificial intelligence systems to recognize if individuals are happy or sad, tired or angry, using a photographic repository of more than 6 million faces.

Recent advances in AI-powered computer vision have accelerated the race for self-driving cars and powered the increasingly sophisticated photo-tagging features found on Facebook and Google. But as these prying AI “eyes” find new applications in store checkout lines, police body cameras and war zones, the tech companies developing them are struggling to balance business opportunities with difficult moral decisions that could turn off customers or their own workers.

El Kaliouby said it’s not hard to imagine using real-time face recognition to pick up on dishonesty — or, in the hands of an authoritarian regime, to monitor reaction to political speech in order to root out dissent. But the small firm, which spun off from a Massachusetts Institute of Technology research lab, has set limits on what it will do.

The company has shunned “any security, airport, even lie-detection stuff,” el Kaliouby said. Instead, Affectiva has partnered with automakers trying to help tired-looking drivers stay awake, and with consumer brands that want to know whether people respond to a product with joy or disgust.

Such queasiness reflects new qualms about the capabilities and possible abuses of all-seeing, always-watching AI camera systems — even as authorities are growing more eager to use them.

In the immediate aftermath of Thursday’s deadly shooting at a newspaper in Annapolis, Maryland, police said they turned to face recognition to identify the uncooperative suspect. They did so by tapping a state database that includes mug shots of past arrestees and, more controversially, everyone who registered for a Maryland driver’s license.

Initial information given to law enforcement authorities said that police had turned to facial recognition because the suspect had damaged his fingerprints in an apparent attempt to avoid identification. That report turned out to be incorrect and police said they used facial recognition because of delays in getting fingerprint identification.

In June, Orlando International Airport announced plans to require face-identification scans of passengers on all arriving and departing international flights by the end of this year. Several other U.S. airports have already been using such scans for some departing international flights.

Chinese firms and municipalities are already using intelligent cameras to shame jaywalkers in real time and to surveil ethnic minorities, subjecting some to detention and political indoctrination. Closer to home, the overhead cameras and sensors in Amazon’s new cashier-less store in Seattle aim to make shoplifting obsolete by tracking every item shoppers pick up and put back down.

Concerns over the technology can shake even the largest tech firms. Google, for instance, recently said it will exit a defense contract after employees protested the military application of the company’s AI technology. The work involved computer analysis of drone video footage from Iraq and other conflict zones.

Google guidelines

Similar concerns about government contracts have stirred up internal discord at Amazon and Microsoft. Google has since published AI guidelines emphasizing uses that are “socially beneficial” and that avoid “unfair bias.”

Amazon, however, has so far deflected growing pressure from employees and privacy advocates to halt Rekognition, a powerful face-recognition tool it sells to police departments and other government agencies.

Saying no to some work, of course, usually means someone else will do it. The drone-footage project involving Google, dubbed Project Maven, aimed to speed the job of looking for “patterns of life, things that are suspicious, indications of potential attacks,” said Robert Work, a former top Pentagon official who launched the project in 2017.

While it hurts to lose Google because they are “very, very good at it,” Work said, other companies will continue those efforts.

Commercial and government interest in computer vision has exploded since breakthroughs earlier in this decade using a brain-like “neural network” to recognize objects in images. Training computers to identify cats in YouTube videos was an early challenge in 2012. Now, Google has a smartphone app that can tell you which breed.

A major research meeting — the annual Conference on Computer Vision and Pattern Recognition, held in Salt Lake City in June — has transformed from a sleepy academic gathering of “nerdy people” to a gold rush business expo attracting big companies and government agencies, said Michael Brown, a computer scientist at Toronto’s York University and a conference organizer.

Brown said researchers have been offered high-paying jobs on the spot. But few of the thousands of technical papers submitted to the meeting address broader public concerns about privacy, bias or other ethical dilemmas. “We’re probably not having as much discussion as we should,” he said.

Not for police, government

Startups are forging their own paths. Brian Brackeen, the CEO of Miami-based facial recognition software company Kairos, has set a blanket policy against selling the technology to law enforcement or for government surveillance, arguing in a recent essay that it “opens the door for gross misconduct by the morally corrupt.”

Boston-based startup Neurala, by contrast, is building software for Motorola that will help police-worn body cameras find a person in a crowd based on what they’re wearing and what they look like. CEO Max Versace said that “AI is a mirror of the society,” so the company chooses only principled partners.

Researchers, led by one of Indian-origin, have developed a new technology that can clean water twice as fast as commercially available ultrafiltration membranes, an advance that brings hope for countries like India where clean drinking water is a big issue.

According to a team from the Washington University in St. Louis, more than one in 10 people in the world lack basic drinking water access, and by 2025, half of the world’s population will be living in water-stressed areas.

The team led by Srikanth Singamaneni, Professor at the varsity, developed an ultrafiltration membrane using graphene oxide and bacterial nanocellulose that they found to be highly efficient, long-lasting and environment-friendly.

The membrane technology purifies water while preventing biofouling, or build up of bacteria and other harmful micro-organisms that reduce the flow of water.

The membrane technology purifies water while preventing biofouling. VOA

For the study, published in the journal Environmental Science and Technology, they used bacteria to build such filtering membranes.

The Gluconacetobacter hansenii bacteria is a sugary substance that forms cellulose nanofibres when in water.

The team then incorporated graphene oxide (GO) flakes into the bacterial nanocellulose while it was growing, essentially trapping GO in the membrane to make it stable and durable.

They exposed the membrane to E. coli bacteria, then shone light on the membrane’s surface.

After being irradiated with light for just three minutes, the E. coli bacteria died. The team determined that the membrane quickly heated to above the 70 degrees Celsius required to deteriorate the cell walls of E. coli bacteria.

While the bacteria are killed, the researchers had a pristine membrane with a high quality of nanocellulose fibres that was able to filter water twice as fast as commercially available ultrafiltration membranes under a high operating pressure.

When they did the same experiment on a membrane made from bacterial nanocellulose without the reduced GO, the E. coli bacteria stayed alive.

The new technology is capable of identifying and quantifying different kinds of cyanobacteria, or blue-green algae, as a threat to shut down water systems when it suddenly proliferates. Pixabay

While the researchers acknowledge that implementing this process in conventional reverse osmosis systems is taxing, they propose a spiral-wound module system, similar to a roll of towels.Also Read: India Gets Assistance of Rs 3,420 Crore From Japan
It could be equipped with LEDs or a type of nanogenerator that harnesses mechanical energy from the fluid flow to produce light and heat, which would reduce the overall cost.

If the technique were to be scaled up to a large size, it could benefit many developing countries where clean water is scarce, the researchers noted. (IANS)